SRmatlab

用奇异值分解的方法实现图像压缩，有助于初学者了解奇异值分解的应用(Using singular value decomposition method to achieve image compression will help beginners understand the application of singular value decomposition)

包括最原始的分数阶微分方法，自适应分数阶微分法，非整数步长的方法。对学习分数阶微分的人是个很好的资料代码。(It includes the most original fractional differential method, adaptive fractional differential method, and non integer step length method. It is a good data code for people learning fractional differential.)

说明：  用matlab写的分水岭算法用于图像分割写的不是很好有需要的看看吧(using Matlab was a watershed for image segmentation algorithm was not very good in need and let's see it)

数字图像处理中的sobel算子Matlab程序(Digital image processing in Matlab procedure sobel operator)

说明：  张正相机标定，用c++编程，亲证有用，里面有实际的图片，大家可以直接俄使用(Zhang zheng method it is very useful for camera detecting and it contains many pictures i hope you will get help from it)

人脸跟踪的一些主流算法的matlab实现(face tracking algorithm for the mainstream to achieve the Matlab)

说明：  准确检测图像中的高光区域，并对检测出的高光区域的高光进行去除(Detect highlights, remove highlights)

本文主要是用matlab提供的小波包对图像进行分解、压缩、重构(This article is mainly used to provide matlab wavelet packet decomposition of images, compression, Reconstruction)

三维时域有限差分法结合UPML吸收边界条件模拟程序(Three-dimensional finite-difference time-domain method combined with UPML absorbing boundary conditions)

摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)